Effect of sowing windows on yield, economics and growing degree days on varieties of green gram (Vigna radiata L.)
Bibliographic record
Abstract
Green gram (Vigna radiata L.) is a short day plant and generally requires fairly hot conditions for its optimum growth and yield. Crop growth and development are closely related with energy requirement parameter such as growing degree days (GDD) which ultimately affect yield and economics. Therefore, experiment was conducted on effect of sowing windows on yield, economics and growing degree days on varieties of green gram (Vigna radiata L.) during kharif-2023 at Agronomy farm, College of Agriculture, Nagpur. The experiment was laid out in split plot design with three sowing windows i.e. 26th MW, 27th MW and 28th MW as main plot treatments and three varieties i.e. PKV Green Gold, PKV Moong-8802 and Kopergaon as sub-plot treatments and replicated thrice with spacing of 30 cm x 10 cm. Other operations were carried out as per recommendations. Results revealed that, 26th MW produces significantly highest grain and straw yield, gross monetary returns, net monetary returns, B:C ratio and accumulated higher GDD as compared to 27th and 28th MW. In case of varieties PKV Green Gold produces highest grain and straw yield, gross monetary returns, net monetary returns, B:C ratio and accumulated higher GDD as compared to PKV Moong-8802 and Kopergaon.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".